..Moreover, it directly provides information on the spatial position correspondence or variability of the activated regions across subjects, which is difficult to obtain in standard voxel-based analyses...

High level group analysis of FMRI data based on Dirichlet process mixture models

..Finally, inter-subject correspondences are computed with Bayesian Network models. We show the power of the technique on both simulated and real datasets and compare it with standard inference techniques...

..We explore a dataset acquired while subjects were involved in several cognitive and sensori-motor processes, and show that this representation allows to classify subjects into sub-groups on the basis of their BFL activity...

Enhancing the reproducibility of group analysis with randomized brain parcellations

..We show that we can obtain groups (or cliques) of parcels that well summarize inter-subject activations. We also show that the spatial relaxation embedded in our procedure improves the sensitivity of random-effect analysis...

..In addition, on a specific transfer situation involving different scanners at different locations, we show that voxel selection based on transfer learning leads to higher detection power on small cohorts...

..We conclude that adding matter information consistently improves the quantitative analysis of BOLD responses in some areas of the brain, particularly those where accurate inter-subject registration remains challenging...

Challenging the estimation of cortical activity from MEG with simulated fMRI-constrained retinotopic maps